We recently revealed new data on the impact of personalized product recommendations for retailers. Among our findings: Visits where the shopper clicked a recommendation comprise just 7% of visits, but create 24% of orders and 26% of revenue. Also impressive is the revelation that purchases where a recommendation was clicked saw a 10% higher average order value, and the per-visit spend of a shopper who clicks a recommendation is five times higher.

Check out this video from this week’s Dreamforce conference, featuring our Senior Vice President of Data Science Rama Ramakrishnan and Product Marketing Manager Hannah Egan, discussing all the AI buzz at Dreamforce, and much more.

On the surface, artificial intelligence and AI-based personalization may seem daunting. But a core tenant of Salesforce Einstein is the ease with which it can be implemented. In this Q&A, Rama demystifies the key concepts of AI and personalization for the non-data scientists among us. Get the complete report, Personalization in Shopping, for more data, charts, and next steps to get started on your AI journey.

Q: Why is personalization so important, and in fact necessary, in today’s ecommerce environment?

Rama: If your catalog has more than a few dozen products, it’s not easy for customers to find what they’re looking for. And if today’s impatient shopper can’t find what they want in a click or two, they will leave you. That’s why personalization is super important.

But despite its clear importance, a fair number of ecommerce sites still don’t use personalization. I am shocked by this and believe these sites are doing themselves a grave disservice.

Q: Implementing personalization can seem daunting. What’s the simplest way for a retailer to get started?

Rama: Take a look at your competitors. I guarantee that your best- in-class peers are already using personalization, so show these sites to your boss. Then dip your toes in the water. On your product detail page, start by incorporating a simple recommendation zone showing additional products that customers may also like. By recommending products similar to the product they’re looking at, you’ve quickly given them more choices and paths forward to purchase.

It doesn’t have to be all or nothing — test gradually. Try recommendations on a few product detail pages, not your entire site. Start small and, if something doesn’t work or your strategy needs further development, you can revert your site back quickly.

After you’ve experienced success with early personalization efforts, you can test predictive search, which gives two people searching for the same thing different search results, based on their browsing and purchasing history. The possibilities of personalization are endless.

“By helping shoppers quickly find the products they actually care about, personalization is driving real growth. It’s nothing less than a retail superpower.” – Rama Ramakrishnan

Q: What’s your advice for merchants who are nervous to give up some control over their site to AI engine?

Rama: Most product recommendation systems, including Commerce Cloud’s, let merchants override or constrain recommendations when needed. For example, you could tell the system not to recommend certain products or brands. You’ll  find that the rules are flexible enough to allay any concerns, so don’t let these qualms sway you from trying personalization. You’d be leaving money on the table if you don’t give it a try.

Q: What’s the future of AI in retail?

Rama: When personalization becomes so woven into the fabric of the shopping experience that the shopper doesn’t realize she is being personalized to, that’s when we have arrived. The future of AI will be that seamless, pervasive impact on every shopper journey.

Over the next few years, I anticipate a world where two different visitors to an ecommerce site receive completely different and tailored experiences, from personalized navigation and personalized pricing to personalized promotions. As long as shoppers have any sort of prior behavior we can learn from, their experience will be truly unique.

Q: How can retailers change their mindsets to prepare for this kind of technology?

Rama: It might sound crazy coming from a data scientist, but retailers must abandon the notion that they must collect a lot of data  first. You likely already have enough data to enact some powerful personalization. So you just have to dive in, and your efforts will become smarter over time.

Want more insights on the impact of personalized recommendations and stories from retail trailblazers who are taking full advantage of AI? Download Personalization in Shopping.